├── .gitignore
├── README.md
├── setup.py
├── tests
├── test_prefixtree.py
└── test_wordcut.py
└── wordcut
├── LICENSE
├── LICENSE-DICT
├── __init__.py
├── bigthai.txt
├── dict.txt
└── example.py
/.gitignore:
--------------------------------------------------------------------------------
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2 | __pycache__/
3 | *.py[cod]
4 |
5 | # C extensions
6 | *.so
7 |
8 | # Distribution / packaging
9 | .Python
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17 | lib/
18 | lib64/
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21 | var/
22 | *.egg-info/
23 | .installed.cfg
24 | *.egg
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58 |
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/README.md:
--------------------------------------------------------------------------------
1 | wordcutpy
2 | =========
3 | wordcutpy is a simple Thai word breaker written in Python 3+
4 |
5 | Installation
6 | ------------
7 |
8 | ````
9 | pip install wordcutpy
10 | ````
11 |
12 |
13 | Example
14 | -------
15 |
16 | ### Conventional verison
17 |
18 | ````python
19 | #! -*- coding: UTF8 -*-
20 | from wordcut import Wordcut
21 | if __name__ == '__main__':
22 | with open('bigthai.txt', encoding="UTF-8") as dict_file:
23 | word_list = list(set([w.rstrip() for w in dict_file.readlines()]))
24 | wordcut = Wordcut(word_list)
25 | print(wordcut.tokenize("กากา cat หมา"))
26 | ````
27 |
28 |
29 | ### Simplified version
30 |
31 |
32 | ````python
33 | #! -*- coding: UTF8 -*-
34 | from wordcut import Wordcut
35 | wordcut = Wordcut.bigthai()
36 | print(wordcut.tokenize("กากา cat หมา"))
37 | ````
38 |
39 | Test
40 | ----
41 |
42 | ### Run tests
43 |
44 | ````shell
45 | python -m unittest discover -s tests
46 | ````
47 |
48 |
--------------------------------------------------------------------------------
/setup.py:
--------------------------------------------------------------------------------
1 | from setuptools import setup
2 |
3 | setup(name='wordcutpy',
4 | version='0.1.2',
5 | description='Thai word tokenizer written in Python',
6 | url='https://github.com/veer66/wordcutpy.git',
7 | author='Vee Satayamas',
8 | author_email='vsatayamas@gmail.com',
9 | license='LGPLv3',
10 | package_data={'': ['LICENSE', 'LICENSE-DICT', 'README.md', 'bigthai.txt', 'dict.txt']},
11 | include_package_data=True,
12 | packages=['wordcut'],
13 | zip_safe=False)
14 |
--------------------------------------------------------------------------------
/tests/test_prefixtree.py:
--------------------------------------------------------------------------------
1 | import unittest
2 | import sys
3 | import os
4 | sys.path.append(os.path.abspath('..'))
5 | from wordcut import PrefixTree
6 |
7 | class TestPrefixTree(unittest.TestCase):
8 | def test_building_prefix_tree_with_none(self):
9 | pt = PrefixTree(None)
10 | self.assertEqual(pt.lookup(0,0,"A"), None)
11 |
12 | def test_basic(self):
13 | self.dix = [("B", "P2"),
14 | ("A", "P1")]
15 | pt = PrefixTree(self.dix)
16 |
17 | self.assertEqual(pt.lookup(0,0,"A"),(0,True,"P1"))
18 |
19 | def test_longer(self):
20 | self.dix = [("B", "P2"),
21 | ("ABC", "P1")]
22 | pt = PrefixTree(self.dix)
23 |
24 | self.assertEqual(pt.lookup(0,0,"A"),(0,False,None))
25 | self.assertEqual(pt.lookup(0,2,"C"),(0,True,"P1"))
26 |
--------------------------------------------------------------------------------
/tests/test_wordcut.py:
--------------------------------------------------------------------------------
1 | import unittest
2 | import sys
3 | import os
4 | sys.path.append(os.path.abspath('..'))
5 | from wordcut import Wordcut
6 |
7 | class TestWordcut(unittest.TestCase):
8 | def setUp(self):
9 | self.wordcut = Wordcut.bigthai()
10 |
11 | def test_empty_input(self):
12 | self.assertEqual(self.wordcut.tokenize(""),[])
13 |
14 | def test_none_input(self):
15 | self.assertEqual(self.wordcut.tokenize(None),[])
16 |
17 | def test_simple_one(self):
18 | self.assertEqual(self.wordcut.tokenize("ฉันกิน"),
19 | ["ฉัน", "กิน"])
20 |
21 | def test_single_unk(self):
22 | self.assertEqual(self.wordcut.tokenize("ฬฬฬ"),
23 | ["ฬฬฬ"])
24 |
25 | def test_simple_roman_without_space(self):
26 | self.assertEqual(self.wordcut.tokenize("ฬฬROฬฬ"),
27 | ["ฬฬ", "RO", "ฬฬ"])
28 |
29 | def test_simple_space(self):
30 | self.assertEqual(self.wordcut.tokenize("ฬฬ มม"),
31 | ["ฬฬ", " ", "มม"])
32 |
--------------------------------------------------------------------------------
/wordcut/LICENSE:
--------------------------------------------------------------------------------
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545 | That's all there is to it!
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547 |
548 |
--------------------------------------------------------------------------------
/wordcut/__init__.py:
--------------------------------------------------------------------------------
1 | """wordcutpy is a word tokenizer written in Python."""
2 |
3 | import re
4 |
5 |
6 | class PrefixTree:
7 | """PrefixTree is a hash tree for storing and searching word list."""
8 |
9 | def __init__(self, members_with_payload):
10 | """Prefix tree is constructed from sorted members with payload."""
11 | self.tab = {}
12 | if members_with_payload is None:
13 | return None
14 | sorted_members_with_payload = sorted(members_with_payload,
15 | key=lambda i: i[0])
16 |
17 | for i in range(len(sorted_members_with_payload)):
18 | members, payload = sorted_members_with_payload[i]
19 | row_no = 0
20 | for j in range(len(members)):
21 | is_terminal = len(members) == j + 1
22 | member = members[j]
23 | key = (row_no, j, member)
24 | if key in self.tab:
25 | row_no = self.tab[key][0]
26 | else:
27 | val = (i, is_terminal, payload if is_terminal else None)
28 | self.tab[key] = val
29 | row_no = i
30 |
31 | def lookup(self, i, offset, member):
32 | """Lookup is done by searching an element of members in the tree."""
33 | key = (i, offset, member)
34 | if key not in self.tab:
35 | return None
36 | return self.tab[key]
37 |
38 |
39 | UNK = 1
40 | DICT = 2
41 | INIT = 3
42 | LATIN = 4
43 | PUNC = 5
44 |
45 |
46 | def is_better(link0, link1):
47 | """Links are compared by their properies."""
48 | if link0 is None:
49 | return True
50 |
51 | if link1["unk"] < link0["unk"]:
52 | return True
53 |
54 | if link1["w"] < link0["w"]:
55 | return True
56 |
57 | return False
58 |
59 |
60 | class LatinTransducer:
61 | """Latin transducer detects latin tokens."""
62 |
63 | def __init__(self):
64 | """Latin transducer is constructed by letting pointers to be None."""
65 | self.latin_s = None
66 | self.latin_e = None
67 |
68 | def update(self, ch, i, s):
69 | """Update by feeding a character, its position, and the string."""
70 | if self.latin_s is None:
71 | if re.match("[A-Za-z]", ch):
72 | self.latin_s = i
73 | else:
74 | if re.match("[A-Za-z]", ch):
75 | if i + 1 == len(s) or not re.match("[A-Za-z]", s[i + 1]):
76 | self.latin_e = i + 1
77 | else:
78 | self.latin_s = None
79 | self.latin_e = None
80 |
81 | def create_link(self, path):
82 | """Pointers are used for creating a link."""
83 | if self.latin_s is not None and self.latin_e is not None:
84 | p_link = path[self.latin_s]
85 | _link = {"p": self.latin_s,
86 | "w": p_link["w"] + 1,
87 | "unk": p_link["unk"],
88 | "type": LATIN}
89 | return _link
90 | return None
91 |
92 |
93 | class PuncTransducer:
94 | """Punc Transducer detects puncuation tokens."""
95 |
96 | def __init__(self):
97 | """Punc Transducer is constructed by letting pointers to be None."""
98 | self.punc_s = None
99 | self.punc_e = None
100 |
101 | def update(self, ch, i, s):
102 | """Update by feeding a character, its position, and the string."""
103 | if self.punc_s is None:
104 | if ch == " ":
105 | self.punc_s = i
106 | else:
107 | if ch == " ":
108 | if len(s) == i + 1 or s[i + 1] != " ":
109 | self.punc_e = i + 1
110 | else:
111 | self.punc_s = None
112 | self.punc_e = None
113 |
114 | def create_link(self, path):
115 | """Pointers are used for creating a link."""
116 | if self.punc_s is not None and self.punc_e is not None:
117 | p_link = path[self.punc_s]
118 | _link = {"p": self.punc_s,
119 | "w": p_link["w"] + 1,
120 | "unk": p_link["unk"],
121 | "type": PUNC}
122 | return _link
123 | return None
124 |
125 |
126 | def build_path(dix, s):
127 | """Build path constructs word tokenization path."""
128 | left_boundary = 0
129 | dict_acc_list = []
130 |
131 | path = [{"p": None, "w": 0, "unk": 0, "type": INIT}]
132 |
133 | punc_transducer = PuncTransducer()
134 | latin_transducer = LatinTransducer()
135 |
136 | for i, ch in enumerate(s):
137 | dict_acc_list.append({"s": i, "p": 0, "final": False})
138 |
139 | # Update dict acceptors
140 | _dict_acc_list = dict_acc_list
141 | dict_acc_list = []
142 | for acc in _dict_acc_list:
143 | offset = i - acc["s"]
144 | child = dix.lookup(acc["p"], offset, ch)
145 | if child is not None:
146 | child_p, is_final, payload = child
147 | dict_acc_list.append({"s": acc["s"], "p": child_p,
148 | "final": is_final})
149 | latin_transducer.update(ch, i, s)
150 | punc_transducer.update(ch, i, s)
151 |
152 | # select link
153 | link = None
154 |
155 | # links from wordlist
156 | for acc in dict_acc_list:
157 | if acc["final"]:
158 | p_link = path[acc["s"]]
159 | _link = {"p": acc["s"],
160 | "w": p_link["w"] + 1,
161 | "unk": p_link["unk"],
162 | "type": DICT}
163 | if is_better(link, _link):
164 | link = _link
165 |
166 | _link = latin_transducer.create_link(path)
167 | if _link is not None and is_better(link, _link):
168 | link = _link
169 |
170 | _link = punc_transducer.create_link(path)
171 | if _link is not None and is_better(link, _link):
172 | link = _link
173 |
174 | # fallback
175 | if link is None:
176 | p_link = path[left_boundary]
177 | link = {"p": left_boundary,
178 | "w": p_link["w"] + 1,
179 | "unk": p_link["unk"] + 1,
180 | "type": UNK}
181 |
182 | path.append(link)
183 |
184 | if link["type"] != UNK:
185 | if link["type"] == LATIN or link["type"] == PUNC:
186 | left_boundary = i + 1
187 | else:
188 | left_boundary = i
189 |
190 | return path
191 |
192 |
193 | def path_to_tokens(txt, path):
194 | """Path to Token transforms a path to a list of tokens."""
195 | if len(path) < 2:
196 | return None
197 |
198 | e = len(path) - 1
199 | toks = []
200 |
201 | while True:
202 | link = path[e]
203 | s = link["p"]
204 | if s is None:
205 | break
206 | toks.append(txt[s:e])
207 | e = s
208 |
209 | toks.reverse()
210 | return toks
211 |
212 |
213 | def tokenize(dix, txt):
214 | """Tokenize splits a string to a list of tokens."""
215 | if txt is None or txt == "":
216 | return []
217 | path = build_path(dix, txt)
218 | return path_to_tokens(txt, path)
219 |
220 |
221 | class Wordcut:
222 | """Wordcut wraps functions and data related tokenizaion."""
223 |
224 | def __init__(self, wordlist):
225 | """Wordcut is constructed by a sorted list of words."""
226 | self.dix = PrefixTree([(word, None) for word in wordlist])
227 |
228 | @classmethod
229 | def bigthai(cls):
230 | """Bigthai constructs Wordcut based on a big Thai word list."""
231 | import os
232 | "Initialize from bigthai"
233 | fileDir = os.path.dirname(__file__)
234 | filename = os.path.join(fileDir, 'bigthai.txt')
235 | with open(filename, 'r', encoding='utf-8-sig') as dict_file:
236 | word_list = list(set([w.rstrip() for w in dict_file.readlines()]))
237 | word_list.sort()
238 | return cls(word_list)
239 |
240 | def tokenize(self, s):
241 | """Tokenize splits a string to a list of tokens."""
242 | return tokenize(self.dix, s)
243 |
--------------------------------------------------------------------------------
/wordcut/dict.txt:
--------------------------------------------------------------------------------
1 | กา
2 | ขา
3 | หมา
--------------------------------------------------------------------------------
/wordcut/example.py:
--------------------------------------------------------------------------------
1 | #! -*- coding: UTF8 -*-
2 | from wordcut import Wordcut
3 | if __name__ == '__main__':
4 | with open('bigthai.txt') as dict_file:
5 | word_list = list(set([w.rstrip() for w in dict_file.readlines()]))
6 | word_list.sort()
7 | wordcut = Wordcut(word_list)
8 | print(wordcut.tokenize("กากา cat หมา"))
9 |
--------------------------------------------------------------------------------